1. Field of the Invention
The present invention relates to a method and an apparatus for generating three-dimensional data by detecting corresponding points of two two-dimensional images whose contents are similar to each other such as two two-dimensional images captured stereographically with respect to an object using a gradient method, a correlation method or the like.
2. Description of the Prior Art
Conventionally, there are known techniques for generating three-dimensional data from plural two-dimensional image data (a two-dimensional image is hereinafter referred to as an “image” and two-dimensional image data are referred to as “image data” in the present specification) as of an object captured by, for example, using a plurality of cameras. In generating the three-dimensional data, it is necessary to detect to which point of an image an arbitrary point of another image corresponds to, i.e. to detect corresponding points of the images. The correlation method is the most popular method for detecting such corresponding points.
By the correlation method, the corresponding points are detected by setting an image as a standard image and finding an area similar to the standard image from another image. For example, the corresponding points are detected in such a manner by extracting a small area of the standard image as a standard window and detecting, in another image, a window having luminance of points similar to those of points of the standard window. The correlation method has other applications such as a method for detecting the corresponding points by a correlation of luminance on an epipolar line, a method wherein the size of a window is changed and a method wherein a correlation is detected by binarization of an image.
Another known method for detecting the corresponding points is the gradient method. In the gradient method, the corresponding points are detected from luminance gradient of an area adjacent to a point whose coordinate is in common to plural images similar to each other.
The correlation method is superior in detecting corresponding points of an object whose luminance or color gradation is widely varying on its surface. However, any of the above methods are not fully satisfactory for the detection of the corresponding points of an object that is poor in luminance change or an object that is low in contrast. Therefore, the correlation method is not suitable for generating three-dimensional data of a face of a human or the like.
In turn, the gradient method requires shorter calculation time as compared with the correlation method and is superior in detecting the corresponding points in the case of low luminance and low contrast. Further, the gradient method can detect the corresponding points correctly by using subpixels if the object is in an ideal state. However, the gradient method is not competent to differences in luminance or color gradation or CCD noise and has a drawback that an erroneous detection of the corresponding points occurs when there is an occlusion. Therefore, the gradient method is not suitable for generating three-dimensional data of products having a spherical or cylindrical shape, products made from a metal or glass and so on.